We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...
We present new methods to extend data reliability of disks in RAID systems for applications like long term data archival. The proposed solutions extend existing algorithms to detec...
This paper proposes and assesses a new distributed simulation platform for heterogeneous wireless communications. The objective of the ICARUS platform is to investigate cross-layer...
M. Carmen Lucas-Estan, Salva Garrigas, Javier Goz&...
We present SpeedBoost, a natural extension of functional gradient descent, for learning anytime predictors, which automatically trade computation time for predictive accuracy by s...
In this paper, we propose a framework that fuses multiple features for improved action recognition in videos. The fusion of multiple features is important for recognizing actions ...